Spatial networks [1]} are a class of networks where the nodes are embedded in a metric space, meaning that the nodes have associated coordinates that allow to define distances between them. Typically, the edges between the nodes are constructed such that a pair of nodes with a small distance between them have a larger probability of being connected with an edge compared with nodes which are far apart. Many real-world systems can be modeled as spatial networks, including transportation systems [2]}, [3]}, [4]} power-grids [5]}, communications [6]}, urban streets [7]}, [8]} infrastructure [9]}, [10]}, [11]} and brain activity [12]}, [13]}.
It is of particular importance to know whether a network contains a Giant Component (GC), i.e., a connected cluster of nodes whose size, \(M\) , remains greater than \(cN\) , where \(0<c\le 1\)  is some constant, for any \(N\rightarrow \infty \) . The existence of a GC in a network signifies the ability of the network to function properly [14]}, [15]}, [16]}, [17]}.
